Top-10 Artificial Intelligence Startups in Italy
Italy is a country of beautiful chaos. Home to some of the world’s best fashion, cars, and food, the country has been a symbol of joie de vivre for centuries. It is also a country steeped in tradition, with a traditional family model and strong roots in Christianity. Her fun-loving people are known for having a great sense of humor, and nearly everything is fair game to poke fun at – like this colorful story about the origins of the country’s most popular religion. While most people think Jesus was black because he called everybody brother, liked Gospel, and didn’t get a fair trial, it turns out that’s not true. Jesus was actually an Italian. That’s because only an Italian son would live with his mama till he was 30, only an Italian son could think his mama was still a virgin, and only an Italian mama could think her son was God. (Ba dum tsss.)
Focusing in on business, Italy’s economy is sizeable (12th in the world by GDP) but it hasn’t grown much over the past year. The country’s GDP per capita (50th in world rankings) remains right around average when compared to the European Union as a whole. Having a not-so-strong economy doesn’t stop the Italians from partaking in the global AI race, and not unsuccessfully so. The government released a white paper on AI in March 2018 concentrating on how it can facilitate the adoption of AI technologies into public administration, and a consortium of universities established a national laboratory for AI shortly after that. To get an idea of what progress is being made, we queried Crunchbase to take a look at the 10 most funded AI startups in Italy.
|Musixmatch||Natural language processing||Bologna||16.8|
|Thron||Marketing||Piazzola sul Brenta||7.0|
|ELSE Corp||Fashion tech||Milan||2.7|
Founded in 2010, Bologna startup Musixmatch has raised $16.8 million in funding to develop the world’s largest lyrics platform. The app’s 50 million users can search, read, and share lyrics for over 14 million music tracks licensed from the largest recording studios like Sony, Universal, and Warner Chappell. Musixmatch also offers a large-scale lyrics and music vocabulary dataset for companies and researchers looking to unleash machine learning algorithms on all the data in order to create music recommendations, analyze lyrics, and gain general insights. The company’s AI service provides Natural Language Processing (NLP) algorithms that analyze lyrics to reveal the structure, meaning, and emotional content of songs, and they can also find the similarities between concepts and sentiments expressed in different songs. Musixmatch has sales offices in London and San Francisco besides their headquarters in Bologna.
We first came across this next startup in our article on 8 Top-funded Facial Recognition Startups. Founded in 2013, Firenze startup Cynny has raised $14 million to develop an adaptive video platform that recognizes the gender, age, and emotions of users. The platform called MorphCast analyzes users’ facial features and adapts videos and displays to their real-time state, targeting online marketing companies.
The tool is fully web-based without the need to install anything, and it can also be embedded into other websites or apps. The product’s facial recognition accuracy is above 95% for gender and emotions, and Cynny is quick to point out that privacy and data protection are embedded into it. No citizen ratings for Europe just yet.
Founded in 2009, Naples startup Cogisen has raised $8.1 million to develop a generic Cognitive AI Platform that can be implemented into diverse applications. Although Cogisen’s platform can be applied to a number of problems, the company has perfected its analytical capabilities for temporal information (meaning information that changes as time moves forward) and created a compression product for video and visual content using this technology. According to the team, “standard” AI technology analyzes each full frame in a video to discover a pattern whereas Cogisen’s algorithms are able to only look at the relevant parts of each frame, and make up the rest. This method supports quicker processes and less AI training, and results in 40% more file compression without a loss in quality, even in cases of high definition applications and video streaming. Broader use cases include detection of specific action in video, autonomous vehicle decision making processes, and cybersecurity.
Founded in 2014, Firenze startup Travel Appeal has raised $8 million in funding to develop big data analytics for the travel industry. The company collects data from 500 different sources to build the world’s largest travel “data lake,” then unleashes its hungry algorithms on this raw data to come up with meaningful insights provided in the form of dashboards. For example, it might raise this alert for an accommodation owner:
This year’s Berlin film festival will attract 20% more travelers than last year. Suggested price increase would be 15% for the period to gain up to $1,000 more revenue.
Travel Appeal claims its service can increase revenues by 25%, occupancy rates by 12%, and direct bookings by 7%. The company has more than 2,500 clients at the moment coming from the travel industry and a handful of other areas like real estate, banking, and retail. The startup offers a complimentary chatbot service that has also been helping travel agents sell more stuff.
Founded in 2001, Piazzola sul Brenta startup THRON has raised $7 million in funding to create a Digital Asset Management (DAM) marketing application that classifies digital content, distributes it through company channels, and autonomously chooses which pieces of content to show users. The tool is used by marketing folks who can manage all digital content (images, video, audio, etc.) centrally, independent of file type, while the AI takes care of classification and searchability.
The platform manages internal collaborations and approval workflows, measures asset performance, and matches the right assets to the right client segments for publication. THRON is integrated with the largest providers of e-commerce, CRM, intranet, and website publication solutions for further automation possibilities. The tool is used by major global brands and has reportedly reduced content management costs by 75% for the global high fashion brand Valentino.
Founded in 2014, Milan startup ELSE Corp (which stands for Exclusive Luxury Shopping Experience) has raised $2.7 million to develop a fashion technology platform that includes virtual retail, cloud manufacturing, and AI-based product design customization. Targeting brands, retailers, manufacturers, and independent designers, ELSE offers mass product personalization, virtual 3D e-commerce solutions including virtual fitting, and order generation for hybrid and distributed manufacturing of apparel and footwear. The platform can be integrated into any brand’s or retailer’s environment and covers all processes from designing a piece of clothing in 3D to on-demand production and visual merchandising.
ELSE’s AI offering incorporates personal size and style recommendation services that form the basis of its direct-to-consumer business model. The company’s ambition is to transform the fashion industry to a consumer-driven one from the current brand/marketing-driven state using technology. Customization and personalization are strong trends in the market at the moment, even re-igniting the ultra-expensive made-to-measure couture segment. ELSE’s tools are currently in beta testing stage.
Founded in 2015, Milan startup MDOTM has raised $2.3 million to develop AI-driven investment strategies for financial markets. The company’s algorithms analyze different asset classes (like stocks, bonds, etc.) and extract information signals from the background noise of the markets, then build actionable investment strategies on them, exploiting market inefficiencies. MDOTM’s clients are institutional investors including banks, family offices, and asset management companies with average Assets Under Management (AUM) of $9 billion. The team began their journey during university by developing an algorithm to manage their own savings, and have been recognized and supported by Google for Entrepreneurs incubator. We touched on the topic of AI-driven asset allocation before in our article on Robo-Advisors, AI, and Asset Allocation.
Founded in 2014, Milan startup Roialty has raised $2.2 million in funding to develop a customer profiling and digital loyalty marketing platform. The startup leverages real-time social media data to profile individuals based on their virtual interactions, and provides personalized, actionable insights on them. Roialty offers a full suite of products for digital marketing. A digital loyalty platform targets individuals, drives them to stores, and engages customers using gamification. A customer segmentation tool enriches customer data and helps predict buying intentions, while an audience analytics tool optimizes marketing content and engagement with the right influencers.
A social listening module provides aggregated information on brands versus competitors, monitors reputation, and provides consumer insights. All of these are available through Application Programming Interfaces (APIs) and can be integrated with CRM and marketing systems. Roialty’s complimentary consulting services help with implementation and custom projects, and the company has offices in Milan, London, and Hong Kong.
Founded in 2016, Modena startup Axyon AI has raised $1.8 million from the likes of ING Ventures and UniCredit to develop machine learning tools for the financial industry. Axyon offers two products. One is for loan syndication analytics targeting corporate and investment banks. Syndicated loans are high value, complex loans provided by a group of lenders and administered by an arranger bank. Axyon’s SynFinance tool analyzes the entire current and historical syndicated loan market providing pricing trends, volumes, and league tables, predicts investor participation, and generates leads for refinancing, saving a huge amount of manual analysis.
The second product, Axyon IRIS, is for asset managers. It looks at market data, financials, fundamentals, and sentiment data to predict asset return and volatility, asset correlations, and financial ratios over different time horizons. These predictions are essential for investment funds’ short and long-term investment decisions and are directly correlated with their performance. The team collaborates with the University of Modena and Reggio Emilia, Nvidia, and IBM.
Founded in 2017, Genova startup Kellify has raised $1.7 million to create AI algorithms that establish correlations between everyday events and asset prices in the real economy. Kellify aims to introduce more transparent and information-based pricing to traditionally inefficient and hard to price markets like fine art, collectibles, wine, and sports events. The company’s neural networks and unsupervised machine learning algorithms remove cognitive biases from these markets built on information inequality and provide users with the collective intelligence of all market participants. The company is in expansion mode, hiring data scientists, developers, and marketing people at the moment.
We relied on Crunchbase to put together this list, and what we ended up with was a nice spread of startups scattered around some of Italy’s finest cities, with fintech being the most popular application. It’s entirely possible we “missed” some Italian AI startups because they weren’t properly reflected in Crunchbase. If you didn’t update Crunchbase because you were too busy washing down a plate of Asiago d’Allevo with a fine bottle of Brunello di Montalcino, it sounds like you have your priorities straight. Don’t worry. Just drop us a note and the next time one of our MBAs is traveling through your region, we’ll stop by and check out what you’re getting up to. Ciao.
Despite what the pundits say, FAANG stocks (Facebook, Apple, Amazon, Netflix, Google) don't give you real exposure to AI. Read about 7 stocks that give you true pure-play exposure to AI in our guide to investing in AI healthcare companies, freely available to Nanalyze subscribers.